Abstract: Process evolution for robotic process automation (RPA) and RPA workflow micro-optimization are disclosed. Initially, an RPA implementation may be scientifically planned, potentially using artificial intelligence (AI). Embedded analytics may be used to measure, report, and align RPA operations with strategic business outcomes. RPA may then be implemented by deploying AI skills (e.g., in the form of machine learning (ML) models) through an AI fabric that seamlessly applies, scales, manages AI for RPA workflows of robots. This cycle of planning, measuring, and reporting may be repeated, potentially guided by more and more AI, to iteratively improve the effectiveness of RPA for a business. RPA implementations may also be identified and implemented based on their estimated return on investment (ROI).

Abstract: A method for measuring experience quality. The method including: receiving key experience aspects (“KEAs”); administering pre-surveys to a representative subset of the experience audience, including an importance pre-survey requesting relative importance between the KEAs; and perception pre-survey requesting how closely perceptions align with each KEAs; calculating importance weights and perception weights based on the pre-surveys; performing a general survey process that includes surveying the experience audience to provide a quality rating indicating how well each of the KEAs was delivered based on their own experience; and calculating an Experience Index score as a measure of the quality of the experience that is an aggregation of the received quality ratings weighted by at least one of the importance weights or the perception weights.

Abstract: A method and system are disclosed for automatic replenishment of a retail enterprise store, and a computer-readable storage medium. In the method of the present disclosure, historical operational transaction data of at least one store of the same type as the retail enterprise store is used to obtain four indicators of each product of the at least one store, a plurality of target features having an impact on an indicator matrix composed of the four indicators are extracted to provide replenishment suggestions, and the indicator matrix composed of the four indicators is automatically adjusted to update a replenishment model. In the embodiments of the present disclosure, a set of algorithm models can be optimized and customized according to the historical operational transaction data of the store and external environments such as weather changes, business circle customer flow, discount events, etc.

Abstract: In some embodiments, apparatuses and methods provide long term scheduling at a plurality of retail stores including storing a forecasted data over at least eight weekly scheduling periods; determining based on the forecasted data a first baseline hours demand value for each day of a week for each job function of a first set of job functions at a particular retail store; determining based on the forecasted data a second baseline hours demand value for each day of the week for each job function of a second set of job functions at the particular retail store; automatically generating a plurality of fixed schedules for a set of task resources at each of the plurality of retail stores; automatically instructing a user electronic device to display a notification indicating that a first fixed schedule associated with a first task resource is available.

Abstract: A system and method are disclosed for computer vision in-store planogram analysis. The system includes a retail entity comprising a product display area defined by a planogram, and a planogram analyzer comprising a server which trains a machine learning model to generate recommendations to optimize one or more planogram metrics using historical data and computer vision data. The system generates, by the trained machine learning model, recommendations to optimize the one or more planogram metrics, and alters the planogram based on the one or more recommendations. The system further uses the trained machine learning model with a probabilistic optimization technique approximating a global optimum to generate the one or more recommendations to optimize the one or more planogram metrics. The computer vision includes one or more of eyeball movement, eyeball engagement and eyeball lingering time.

Abstract: Aspects of the disclosure relate to intelligent bot performance tracking and analysis. A computing platform may receive a work queue of items to be processed using a bot. The computing platform may receive, in real-time with processing of the work queue using the bot, metadata associated with the work queue. Based on the metadata, the computing platform may assign, in real-time, a value metric associated with completion of each item in the work queue. Based on the assigned value metric, the computing platform may identify a robotic process automation cost associated with processing the work queue via the bot. The computing platform may compare, the robotic process automation cost to a cost to process the work queue via another operation, and determine a performance metric for the bot based on the comparison. The computing platform may dynamically generate and transmit, in real-time, an indication of the determined bot performance metric.

Abstract: Systems and methods of the present disclosure facilitate managing a sale via a sales management system. In some embodiments, the system includes a sales opportunity module and a service ticket translation module. The sales opportunity module may be configured to receive a sales leads data structure comprising at least one sales lead. Based on at least one qualification criterion, the system may be configured to identify a sales lead of the sales lead data structure as a sales opportunity. The service ticket translation module may be configured to select data of the sales opportunity for inclusion in a service ticket. By maintaining the selected data of the sales opportunity, the service ticket translation module may be configured to translate the selected data of the sales opportunity into the service ticket. The service ticket translation module may be configured to provide the service ticket to a service board.

Abstract: A computer program product for prioritizing order fulfillment at a retail sales facility receives purchase request information at a retail sales computing device that includes identifying information and order information for the first customer, receives location information for the first customer, processes the received location information for the first customer together with location information of the retail sales facility to predict an estimated time of arrival (ETA) for the first customer at the retail sales facility, schedules a time interval for acquiring updated location information for the first customer, and places the identifying information, order information and ETA for the first customer in an order fulfillment queue for all current customers. Entries in the order fulfillment queue are ordered in increasing ETA order. ETA is continuously updated for each customer, and thereby the order for fulfilling customer orders in the order fulfillment queue.

Abstract: An online concierge system receives a delivery order containing a list of items, generates a suggested picking sequence for picking the delivery order in a warehouse, and transmits the suggested picking sequence to a mobile device of the shopper. Generating the suggested sequence includes applying a trained item sequence model to the delivery order. Training the item sequence model includes accessing data about a set of historical orders, determining a pairwise distance between each pair of aisles in the warehouse based on the data about the set of historical orders, and generating a distance graph based on the pairwise distance between each pair of aisles in the warehouse. The plurality of nodes represent a plurality of aisles in the warehouse, and the plurality of edges represent pairwise distances between pairs of aisles.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for conditional monitoring using different groups of remote devices. In some implementations, a system accesses data indicating characteristics for a monitoring program that involves data collection from a plurality of remote devices over a communication network. The system identifies a group of candidates for the monitoring program and, based on outcomes of other monitoring programs, the system generates a prediction for a level of compliance of the group with the requirements of the monitoring program. The system generates one or more scores indicative of whether the monitoring program will satisfy one or more predetermined conditions needed for successful completion of the monitoring program. Based on the generated one or more scores, the system provides a notification over the communication network that is indicative of whether the monitoring program will satisfy one or more predetermined conditions.

Abstract: An information processing device includes an estimation unit estimating the number of persons in a facility based on a first number of MAC addresses counted based on first information about MAC addresses collected from radio waves transmitted by first terminals during a first time period, and a learned model, and a determination unit determining a third number of MAC addresses changing randomly, from the first number based on a first half of each of the MAC addresses. The learned model is generated by machine learning teacher data defining a relationship between a second number of MAC addresses counted based on second information about MAC addresses collected from radio waves transmitted from second terminals in the facility during a second time period, and the actual number of persons in the facility. The estimation unit estimates part of the number of the persons based on the third number and the learned model.

Abstract: This disclosure relates to improved systems and methods for predicting the correlation between the performance of an entity and one or more data assets related to that entity. The techniques described herein can be utilized to generate various types of data asset predictions that objectively quantify or measure metrics related to the data assets. In some embodiments, one or more machine learning models can be executed to perform relevancy and/or correlation analyses, and the outputs of the machine learning models can be utilized to generate the data asset predictions. Other embodiments are disclosed herein as well.

Abstract: A device may receive historical project data identifying experiences and/or work product from previous projects and client data identifying a client with a problem, and may process the historical project data and the client data, with machine learning models, to generate recommendations for the problem and confidence scores for the recommendations. The device may process the recommendations and the confidence scores, with an NLG model, to generate a solution to the problem and content for the solution, and may generate a digitized dynamic client solution to the problem based on the solution and the content. The device may provide the digitized dynamic client solution to a user device, and may receive feedback on the digitized dynamic client solution from the user device. The device may generate a final digitized dynamic client solution based on the feedback, and may perform actions based on the final digitized dynamic client solution.

Abstract: Methods for personalized marketing and advertising to a person at a location, such as a retail store. Generally, the methods are for monitoring and analyzing consumer and their purchasing behavior in real-time to drive sales by creating personalized marketing and advertising directed to the consumer.

Abstract: Techniques are described herein for using artificial intelligence (AI) and machine learning (ML) to automate, accelerate, and enhance various aspects of comparative user experience testing. Embodiments interface with generative language models to compare user experiences and summarize the results of the comparison. In some embodiments, automated systems and programmatic processes access a series of analysis contexts, where a context includes a collection of message content fragments. The systems and processes may use the message content fragments for a given context to construct a dialogue with a generative language model to compare separate user experiences based on the results of a set of user experience tests. The output of the generative language model at one stage of the analysis may be combined with content fragments for another context to craft a dialogue at another stage of the analysis and/or to perform additional analyses of the user experiences.

Abstract: The present invention comprises a market exchange platform for connecting manufacturers and merchants in a cost and time efficient manner to reduce the cost of goods and to maximize the sales without creating excess inventory. The system may allow for the tracking of orders from a merchant at the inception of a good order to the sale of the good by the merchant. Tracking of a good may allow for each manufacturer to be rated on their efficiency in terms of both cost and time which may allow for various vendor ratings to be assigned to each of the manufacturers and merchants using the market exchange platform.

Abstract: A computer-implemented method is disclosed for generating insights for improving software workflows, where a workflow corresponds to a sequence of interactions of a user with one or more different user interface screens of software applications to perform a task. Attributes of the workflow associated with quality, efficiency and other attributes are measured by scoring aspects of the workflow and generating reports. The reports may also provide insights on opportunities to automate workflows.

Abstract: A method for payment submission scheduling includes receiving, at an acquirer computing system, an authorization request submitted by a merchant computing system for a transaction, the merchant computing system being associated with a merchant, and the authorization request identifying account information for an account that is associated with a payment card network and an issuer processor; generating a submission schedule to submit the authorization request based on a dataset of historical processing results, the submission schedule identifying a time slot within which the submitted authorization request is to be transmitted to the issuer processor; and transmitting, by the acquirer computing system to an issuer processor, the authorization request, within the time slot identified by the submission schedule.

Abstract: A system and method that enables the ongoing communication, tracking, and management review of feedback among a population of workers and their management.

Abstract: Systems, methods, and computer program products for determining an application status of an applicant for an educational program may include receiving cohort performance data comprising first data entries for participants that have respectively achieved outcomes for the educational program and applicant performance data comprising second data entries for the applicant, calculating adjusted cohort performance data based on the cohort performance data and first data characteristics, providing a predictor model based on the adjusted cohort performance data and the outcomes, sequentially changing predictive parameters of the first data characteristics to create second data characteristics and creating an adjusted predictor model based on the second data characteristics and the outcomes, calculating adjusted applicant performance data based on the applicant performance data and the second data characteristics, and calculating a probability of success for the applicant in the educational program based on the adjust